“Data is the new black” was an apropos statement for RichRelevance chief executive officer and cofounder David Selinger to open with given the number of fashion marketers in the audience.

This story first appeared in the June 19, 2013 issue of WWD. Subscribe Today.

Selinger, an expert in the field of e-commerce data analytics and personalization, may have labeled himself “among the people who are geeky and don’t belong here,” but his services are in demand for fashion retailers ranging from Target to Nordstrom, Saks Fifth Avenue to Barneys New York.

He began his career leading Amazon’s research and development team, implementing the feature that recommends items to buy based on customers’ previous purchases. The program increased Amazon’s annual profits by $50 million in 2003.

“My goal today is to reduce big data down and make it more tangible,” he said of the black analogy, noting that data is timeless, always appropriate and offers a solution when nothing else will do. It also possesses increasing volume, increasing cost for which to store said volume and the ability to derive insights of one’s customers.

“It can redefine our relationship with our customers, and more importantly, it can redefine the way we operate as a business,” he said.

Together with Paco Underhill, author of “Why We Buy: The Science of Shopping,” Selinger identified three attributes of the “superconsumer.” She is more informed, having spent hours on the Internet researching a product before she sets foot into the store. She is also less loyal to brands. “It’s now much more about value exchange and getting the right price and quality, not just the right label,” he said. And, not surprisingly, she is more connected — via computers, mobile devices and social media platforms.

With superconsumers, Selinger said there were several dos and don’ts for retailers. First, figuring out the context of omnichannel, a term he and Underhill coined at the NRF’s 2011 forum to describe the combined multiple ways retail transactions take place. For example, how to credit specific sales associates with customers’ online purchases. Stores can use this information to identify their most loyal and valuable customers when they enter a store, and to find ways to keep them there and get them to buy more. It’s not always about offering a discount, Selinger noted.

“Data is all too frequently confused with coupons and price, but you can also use it to develop a relationship,” he said.

This plays into listening instead of yelling. For example, Selinger noted that Procter & Gamble has 10 employees who respond to all tweets and use the content to change the way it markets to customers.

He advised retailers to be open to testing and optimization, “to blend the art and act of merchandising with the science of data.”

Selinger cited an office goods chain that invested $250,000 in running 25 tests, 20 of which were successful and increased sales by more than $100 million. He also cited the trend toward personalization.

To that end, he advised retailers to not leave their practical instincts behind. For example, sharing a purchase with all your Facebook friends probably won’t achieve much, but sharing a meaningful review with select influencers in one’s network could have major results.

“My mentor Jeff Bezos once told me, ‘At the expense of everything else, don’t focus on your competitors, have a laser focus on your customers.’ With all the data coming at us from every direction, we should focus on the only person who matters, our customer.”

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